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Temporal Fusion Transformers for interpretable multi-horizon time series forecasting

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Cited by:

  1. Ozan Ozyegen & Garima Malik & Mucahit Cevik & Kevin Ioi & Karim El Mokhtari, 2026. "A unified framework for financial commentary prediction," Information Technology and Management, Springer, vol. 27(1), pages 95-111, March.
  2. Frederick Nsambu Kijjambu & Benjamin Musiita & Asaph Kaburura Katarangi & Geoffrey Kahangane & Sheilla Akampwera, 2023. "Determinants of Uganda’s Debt Sustainability: The Public Debt Dynamics Model in Perspective," Journal of Economics and Behavioral Studies, AMH International, vol. 15(4), pages 106-124.
  3. Md. Iftekharul Alam Efat & Petr Hajek & Mohammad Zoynul Abedin & Rahat Uddin Azad & Md. Al Jaber & Shuvra Aditya & Mohammad Kabir Hassan, 2024. "Deep-learning model using hybrid adaptive trend estimated series for modelling and forecasting sales," Annals of Operations Research, Springer, vol. 339(1), pages 297-328, August.
  4. Tom Liu & Stephen Roberts & Stefan Zohren, 2023. "Deep Inception Networks: A General End-to-End Framework for Multi-asset Quantitative Strategies," Papers 2307.05522, arXiv.org.
  5. Bentsen, Lars Ødegaard & Warakagoda, Narada Dilp & Stenbro, Roy & Engelstad, Paal, 2023. "Spatio-temporal wind speed forecasting using graph networks and novel Transformer architectures," Applied Energy, Elsevier, vol. 333(C).
  6. Hoang Anh Nguyen & Nhat Hoang Bach, 2026. "QI-HRNN: a quantum-inspired hybrid framework for resilient currency forecasting under extreme market conditions," Digital Finance, Springer, vol. 8(2), pages 1-40, June.
  7. Yuguang Yan & Gan Li & Qingliang Li & Xiao Chen & Jinlong Zhu, 2026. "Improving Short-term Forecasts of Soil Moisture and Evapotranspiration with Multi-task Learning and Transformer-based Feature Processing," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 40(5), pages 1-17, March.
  8. Nascimento, Erick Giovani Sperandio & de Melo, Talison A.C. & Moreira, Davidson M., 2023. "A transformer-based deep neural network with wavelet transform for forecasting wind speed and wind energy," Energy, Elsevier, vol. 278(C).
  9. Jang, Junkyu, 2025. "Selective news selection model for explainable stock prediction via cross-attention integration," Finance Research Letters, Elsevier, vol. 85(PD).
  10. Pegah Eslamieh & Mehdi Shajari & Ahmad Nickabadi, 2023. "User2Vec: A Novel Representation for the Information of the Social Networks for Stock Market Prediction Using Convolutional and Recurrent Neural Networks," Mathematics, MDPI, vol. 11(13), pages 1-26, July.
  11. Zou, Yajie & Chen, Yubin & Xu, Yajiao & Zhang, Hao & Zhang, Siyang, 2024. "Short-term freeway traffic speed multistep prediction using an iTransformer model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 655(C).
  12. Muniz, Rafael Ninno & Stefenon, Stefano Frizzo & Buratto, William Gouvêa & Nied, Ademir & Cardoso, Rodolfo & Yamaguchi, Cristina Keiko & Yow, Kin-Choong, 2025. "Time series forecasting based on multi-criteria optimization for model and filter selection applied to hydroelectric power plants," Energy, Elsevier, vol. 337(C).
  13. Feddersen, Leif & Cleophas, Catherine, 2026. "Hierarchical neural additive models for interpretable demand forecasts," International Journal of Forecasting, Elsevier, vol. 42(1), pages 216-234.
  14. Damian Kisiel & Denise Gorse, 2022. "Portfolio Transformer for Attention-Based Asset Allocation," Papers 2206.03246, arXiv.org.
  15. Keyan Jin & Francisco Javier Blanco‐Encomienda, 2026. "Seasonal Decomposition‐Enhanced Deep Learning Architecture for Probabilistic Forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 45(2), pages 880-891, March.
  16. Shubham Agarwal & Prateek Agrawal & Anurag Allamsetty & Adarsh Attavar & Deekshith B & Gowtham Bellala & Shobhit Bhatnagar & Hardik Choudhari & Vikas Goel & Praveen Gupta & Ananth Kachroo & Jay Kothad, 2026. "Faster, Smarter, Leaner: How Flipkart Optimized Its Supply Chain to Unlock Growth," Interfaces, INFORMS, vol. 56(1), pages 42-57, January.
  17. Carlei, Vittorio & Furia, Donatella & Cascioli, Piera & Manenti, Paolo, 2025. "Macro-founded machine learning models for power market price trend detection," Finance Research Letters, Elsevier, vol. 83(C).
  18. Yoontae Hwang & Stefan Zohren, 2025. "Signature-Informed Transformer for Asset Allocation," Papers 2510.03129, arXiv.org, revised Jan 2026.
  19. Van Gompel, Jonas & Claessens, Bert & Develder, Chris, 2025. "Probabilistic forecasting of power system imbalance using neural network-based ensembles," Applied Energy, Elsevier, vol. 401(PB).
  20. Manikrao Patil & Jaikumar M. Patil & Aniket K. Shahade & Priyanka V. Deshmukh, 2026. "Explainable Multi-source AI Framework for Real-Time Stock Price Monitoring and Prediction," SN Operations Research Forum, Springer, vol. 7(1), pages 1-24, March.
  21. Guo, Qing & Mai, Zishan, 2024. "How do seasonal, significant events, and policies affect China's REE export prices? Based on deep learning perspective," Resources Policy, Elsevier, vol. 96(C).
  22. Houndekindo, Freddy & Ouarda, Taha B.M.J., 2025. "LSTM and Transformer-based framework for bias correction of ERA5 hourly wind speeds," Energy, Elsevier, vol. 328(C).
  23. Dong Zhang & Yangyu Deng & Yakun Liu & Di Zhang, 2026. "Stacking Ensemble Learning for Daily Potential Evapotranspiration using Limited Climate Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 40(4), pages 1-20, March.
  24. Shovon Sengupta & Sunny Kumar Singh & Tanujit Chakraborty, 2025. "Macroeconomic Forecasting for the G7 countries under Uncertainty Shocks," Papers 2510.23347, arXiv.org.
  25. Frank, Johannes, 2023. "Forecasting realized volatility in turbulent times using temporal fusion transformers," FAU Discussion Papers in Economics 03/2023, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
  26. Arash Peik & Mohammad Ali Zare Chahooki & Amin Milani Fard & Mehdi Agha Sarram, 2025. "Adaptive Temporal Fusion Transformers for Cryptocurrency Price Prediction," Papers 2509.10542, arXiv.org.
  27. Tang, Huadu & Kang, Fei & Li, Xinyu & Sun, Yong, 2025. "Short-term photovoltaic power prediction model based on feature construction and improved transformer," Energy, Elsevier, vol. 320(C).
  28. Zheng, Minglei & Man, Junfeng & Wang, Dian & Chen, Yanan & Li, Qianqian & Liu, Yong, 2023. "Semi-supervised multivariate time series anomaly detection for wind turbines using generator SCADA data," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
  29. Sprangers, Olivier & Wadman, Wander & Schelter, Sebastian & de Rijke, Maarten, 2024. "Hierarchical forecasting at scale," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1689-1700.
  30. Feng, Guanxiang & Chen, Yingxue & Gou, Linfeng, 2025. "Multi-scale spatiotemporal feature-assisted physical information graph temporal convolutional network for aero-engine degradation trend prediction," Energy, Elsevier, vol. 340(C).
  31. Dai, Ting-Yu & Niyogi, Dev & Nagy, Zoltan, 2025. "CityTFT: A temporal fusion transformer-based surrogate model for urban building energy modeling," Applied Energy, Elsevier, vol. 389(C).
  32. I Gede Nyoman Mindra Jaya & Henk Folmer & Johan Lundberg, 2024. "A joint Bayesian spatiotemporal risk prediction model of COVID-19 incidence, IC admission, and death with application to Sweden," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 72(1), pages 107-140, January.
  33. Alexios Lekidis & Elpiniki I. Papageorgiou, 2023. "Edge-Based Short-Term Energy Demand Prediction," Energies, MDPI, vol. 16(14), pages 1-20, July.
  34. Jin, Xiao & Lin, Shu-Ling, 2025. "An early prediction model on systemic risk under global risk: Using FinBERT and temporal fusion transformer to multimodal data fusion framework," The North American Journal of Economics and Finance, Elsevier, vol. 76(C).
  35. Wu, Binrong & Yu, Sihao & Peng, Lu & Wang, Lin, 2024. "Interpretable wind speed forecasting with meteorological feature exploring and two-stage decomposition," Energy, Elsevier, vol. 294(C).
  36. Cao, Tingwei & Xu, Yinliang & Liu, Guowei & Tao, Shengyu & Tang, Wenjun & Sun, Hongbin, 2024. "Feature-enhanced deep learning method for electric vehicle charging demand probabilistic forecasting of charging station," Applied Energy, Elsevier, vol. 371(C).
  37. Tuominen, Jalmari & Pulkkinen, Eetu & Peltonen, Jaakko & Kanniainen, Juho & Oksala, Niku & Palomäki, Ari & Roine, Antti, 2024. "Forecasting emergency department occupancy with advanced machine learning models and multivariable input," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1410-1420.
  38. Wu, Binrong & Wang, Lin & Zeng, Yu-Rong, 2022. "Interpretable wind speed prediction with multivariate time series and temporal fusion transformers," Energy, Elsevier, vol. 252(C).
  39. He, Miao & Jiang, Weiwei & Gu, Weixi, 2024. "TriChronoNet: Advancing electricity price prediction with Multi-module fusion," Applied Energy, Elsevier, vol. 371(C).
  40. Matteo Prata & Giuseppe Masi & Leonardo Berti & Viviana Arrigoni & Andrea Coletta & Irene Cannistraci & Svitlana Vyetrenko & Paola Velardi & Novella Bartolini, 2023. "LOB-Based Deep Learning Models for Stock Price Trend Prediction: A Benchmark Study," Papers 2308.01915, arXiv.org, revised Sep 2023.
  41. Shiyu Liu & Ou Liu & Junyang Chen, 2023. "A Review on Business Analytics: Definitions, Techniques, Applications and Challenges," Mathematics, MDPI, vol. 11(4), pages 1-20, February.
  42. Yuanhong Mao & Zhong Ma & Xi Liu & Pengchao He & Bo Chai, 2023. "A Long-Term Prediction Method of Computer Parameter Degradation Based on Curriculum Learning and Transfer Learning," Mathematics, MDPI, vol. 11(14), pages 1-15, July.
  43. Zeng, Huanze & Wu, Binrong & Fang, Haoyu & Lin, Jiacheng, 2025. "Interpretable wind speed forecasting through two-stage decomposition with comprehensive relative importance analysis," Applied Energy, Elsevier, vol. 392(C).
  44. Tiantian Tu, 2025. "Bridging Short- and Long-Term Dependencies: A CNN-Transformer Hybrid for Financial Time Series Forecasting," Papers 2504.19309, arXiv.org.
  45. He, Wenbin & Liu, Ting & Ming, Wuyi & Li, Zongze & Du, Jinguang & Li, Xiaoke & Guo, Xudong & Sun, Peiyan, 2024. "Progress in prediction of remaining useful life of hydrogen fuel cells based on deep learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
  46. Tom Liu & Stefan Zohren, 2023. "Multi-Factor Inception: What to Do with All of These Features?," Papers 2307.13832, arXiv.org.
  47. Wei, Jiangxia & Zhang, Weiqiang & Zhang, Wenjie & Ren, Mifeng & Xu, Xinying & Cheng, Lan, 2025. "DBSTN: A dual-branch spatio-temporal network for wind power prediction using multi-modal fusion," Energy, Elsevier, vol. 341(C).
  48. Yu, Hanxin & Chen, Shanlin & Chu, Yinghao & Li, Mengying & Ding, Yueming & Cui, Rongxi & Zhao, Xin, 2024. "Self-attention mechanism to enhance the generalizability of data-driven time-series prediction: A case study of intra-hour power forecasting of urban distributed photovoltaic systems," Applied Energy, Elsevier, vol. 374(C).
  49. Runyao Yu & Yuchen Tao & Fabian Leimgruber & Tara Esterl & Jochen Stiasny & Derek W. Bunn & Qingsong Wen & Hongye Guo & Jochen L. Cremer, 2025. "OrderFusion: Encoding Orderbook for End-to-End Probabilistic Intraday Electricity Price Forecasting," Papers 2502.06830, arXiv.org, revised May 2026.
  50. Xiang Ao & Jingxuan Zhang & Xinyu Zhao, 2026. "Dynamic Forecasting and Temporal Feature Evolution of Stock Repurchases in Listed Companies Using Attention-Based Deep Temporal Networks," Papers 2604.09650, arXiv.org.
  51. Jaemoo Hong & Yoon Min Hwang, 2025. "Long short-term memory networks in learning memory inconsistencies of stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-50, December.
  52. Gomez, William & Wang, Fu-Kwun & Chou, Jia-Hong, 2024. "Li-ion battery capacity prediction using improved temporal fusion transformer model," Energy, Elsevier, vol. 296(C).
  53. Chou, Jia-Hong & Wang, Fu-Kwun, 2025. "Future prediction on the remaining useful life of proton exchange membrane fuel using temporal fusion transformer model," Renewable Energy, Elsevier, vol. 247(C).
  54. Theodoros Zafeiriou & Dimitris Kalles, 2024. "Off-the-Shelf Neural Network Architectures for Forex Time Series Prediction come at a Cost," Papers 2405.10679, arXiv.org.
  55. Remi Genet & Hugo Inzirillo, 2025. "LEMs: A Primer On Large Execution Models," Papers 2509.25211, arXiv.org.
  56. Zhao, Yongning & Liao, Haohan & Zhao, Yuan & Pan, Shiji, 2025. "Data-augmented trend-fluctuation representations by interpretable contrastive learning for wind power forecasting," Applied Energy, Elsevier, vol. 380(C).
  57. Juan Laborda & Sonia Ruano & Ignacio Zamanillo, 2023. "Multi-Country and Multi-Horizon GDP Forecasting Using Temporal Fusion Transformers," Mathematics, MDPI, vol. 11(12), pages 1-26, June.
  58. Pinheiro, Marco G. & Madeira, Sara C. & Francisco, Alexandre P., 2023. "Short-term electricity load forecasting—A systematic approach from system level to secondary substations," Applied Energy, Elsevier, vol. 332(C).
  59. Sun, Wenjie & Wu, Chengke & Xie, Chengde & Wang, Xikang & Guo, Yuanjun & Tang, Yongbing & Zhang, Yanhui & Li, Kang & Du, Guanhao & Yang, Zhile & Yao, Wenjiao, 2025. "Fine-tuning enables state of health estimation for lithium-ion batteries via a time series foundation model," Energy, Elsevier, vol. 318(C).
  60. Wu, Binrong & Lin, Jiacheng & Liu, Rui & Wang, Lin, 2026. "A multi-dimensional interpretable wind speed forecasting model with two-stage feature exploring," Renewable Energy, Elsevier, vol. 256(PB).
  61. He, Jinhua & Hu, Zechun & Wang, Songpo & Mujeeb, Asad & Yang, Pengwei, 2024. "Windformer: A novel 4D high-resolution system for multi-step wind speed vector forecasting based on temporal shifted window multi-head self-attention," Energy, Elsevier, vol. 310(C).
  62. Zhang, Hanyu & Zandehshahvar, Reza & Tanneau, Mathieu & Van Hentenryck, Pascal, 2025. "Weather-informed probabilistic forecasting and scenario generation in power systems," Applied Energy, Elsevier, vol. 384(C).
  63. Fan Zhang & Jiabin Luo & Zheng Zhang & Shuanghong Huang & Zhipeng Liu & Yu Chen, 2026. "Beyond Visual Realism: Toward Reliable Financial Time Series Generation," Papers 2601.12990, arXiv.org.
  64. Gupta, Abhijit, 2025. "Decoding Futures Price Dynamics: A Regularized Sparse Autoencoder for Interpretable Multi-Horizon Forecasting and Factor Discovery," OSF Preprints 4rzky_v1, Center for Open Science.
  65. Abdelfatah, Omar Sharafeldin Mohamed, 2026. "AI-Driven Demand Forecasting and Its Impact on Inventory Optimization," SocArXiv uw57j_v1, Center for Open Science.
  66. Meisenbacher, Stefan & Phipps, Kaleb & Taubert, Oskar & Weiel, Marie & Götz, Markus & Mikut, Ralf & Hagenmeyer, Veit, 2025. "AutoPQ: Automating quantile estimation from point forecasts in the context of sustainability," Applied Energy, Elsevier, vol. 392(C).
  67. Liu, Dinggao & Chen, Kaijie & Cai, Yi & Tang, Zhenpeng, 2024. "Interpretable EU ETS Phase 4 prices forecasting based on deep generative data augmentation approach," Finance Research Letters, Elsevier, vol. 61(C).
  68. Gou, Liangjie & Yang, Zhaozhong & Min, Chao & Yi, Duo & Li, Xiaogang & Kong, Bing, 2024. "A novel domain adaptation method with physical constraints for shale gas production forecasting," Applied Energy, Elsevier, vol. 371(C).
  69. Ali Atiah Alzahrani, 2025. "Multi-Agent Regime-Conditioned Diffusion (MARCD) for CVaR-Constrained Portfolio Decisions," Papers 2510.10807, arXiv.org, revised Nov 2025.
  70. Sengupta, Shovon & Chakraborty, Tanujit & Singh, Sunny Kumar, 2025. "Forecasting CPI inflation under economic policy and geopolitical uncertainties," International Journal of Forecasting, Elsevier, vol. 41(3), pages 953-981.
  71. Zhuang, Xinyu & Wang, Wendong & Su, Yuliang & Shi, Menghe & Dai, Zhenxue, 2025. "Life-cycle prediction and optimization of sequestration performance in CO2 mixture huff-n-puff development for tight hydrocarbon reservoirs," Applied Energy, Elsevier, vol. 388(C).
  72. Arash Peik & Mohammad Ali Zare Chahooki & Amin Milani Fard & Mehdi Agha Sarram, 2024. "Leveraging Time Series Categorization and Temporal Fusion Transformers to Improve Cryptocurrency Price Forecasting," Papers 2412.14529, arXiv.org.
  73. Singh, S. & Budarapu, P.R., 2024. "Deep machine learning approaches for battery health monitoring," Energy, Elsevier, vol. 300(C).
  74. Guo, Zhonghui & Feng, Chang & Yang, Liu & Liu, Qing, 2025. "An interpretable coupled model (SWAT-STFT) for multispatial-multistep evapotranspiration prediction in the river basin," Agricultural Water Management, Elsevier, vol. 318(C).
  75. Xu, Shilin & Liu, Yang & Jin, Chun, 2023. "Forecasting daily tourism demand with multiple factors," Annals of Tourism Research, Elsevier, vol. 103(C).
  76. Kieran Wood & Stephen J. Roberts & Stefan Zohren, 2026. "DeePM: Regime-Robust Deep Learning for Systematic Macro Portfolio Management," Papers 2601.05975, arXiv.org.
  77. Li, Xin & Xu, Yechi & Law, Rob & Wang, Shouyang, 2024. "Enhancing tourism demand forecasting with a transformer-based framework," Annals of Tourism Research, Elsevier, vol. 107(C).
  78. Vegard H. Larsen & Leif Anders Thorsrud, 2026. "Using Transformers and Reinforcement Learning as Narrative Filters in Macroeconomics," Working Papers No 02/2026, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  79. O. Didkovskyi & A. Vidali & N. Jean & G. Le Pera, 2026. "Temporal-Aligned Meta-Learning for Risk Management: A Stacking Approach for Multi-Source Credit Scoring," Papers 2601.07588, arXiv.org.
  80. Niu, Zhewen & Han, Xiaoqing & Zhang, Dongxia & Wu, Yuxiang & Lan, Songyan, 2024. "Interpretable wind power forecasting combining seasonal-trend representations learning with temporal fusion transformers architecture," Energy, Elsevier, vol. 306(C).
  81. Thabang Mathonsi & Terence L. van Zyl, 2021. "A Statistics and Deep Learning Hybrid Method for Multivariate Time Series Forecasting and Mortality Modeling," Forecasting, MDPI, vol. 4(1), pages 1-25, December.
  82. Yulong Bai & Xianbao Tan & Xiaoxin Yue, 2025. "A Hybrid Mamba Architecture with Graph Convolution and Convolutional Self-Attention for Multivariate Water Quality Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 39(13), pages 7075-7107, October.
  83. Yousef Adeli Sadabad & Mohammad Reza Hesamzadeh & Gyorgy Dan & Matin Bagherpour & Darryl R. Biggar, 2025. "Driver Identification and PCA Augmented Selection Shrinkage Framework for Nordic System Price Forecasting," Papers 2509.18887, arXiv.org.
  84. Nie, Xiaobo & Pan, Yongjun & Zhang, Yongzhi & Luo, Zhenning & Wang, Shuxin, 2026. "Battery health prediction under data scarcity: A cross-domain physics-informed 5-shot framework with GRU-Transformer," Applied Energy, Elsevier, vol. 402(PB).
  85. Wang, Yun & Xu, Houhua & Zou, Runmin & Zhang, Fan & Hu, Qinghua, 2024. "Dynamic non-constraint ensemble model for probabilistic wind power and wind speed forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 204(C).
  86. Wang, Wenyang & Luo, Yuping & Xu, Yuqiang & Liu, Danzhu & Zhou, Jibin & Shao, Peng, 2025. "SPPformer: A transformer-based model with a sparse attention mechanism for comprehensive and interpretable ship price analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 199(C).
  87. Florindo, Joao B. & Lima, Reneé Rodrigues & dos Santos, Francisco Alves & Alves, Jerson Leite, 2025. "GHENet: Attention-based Hurst exponents for the forecasting of stock market indexes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 667(C).
  88. Dong, Hanjiang & Zhu, Jizhong & Li, Shenglin & Wu, Wanli & Zhu, Haohao & Fan, Junwei, 2023. "Short-term residential household reactive power forecasting considering active power demand via deep Transformer sequence-to-sequence networks," Applied Energy, Elsevier, vol. 329(C).
  89. Zhu, Leyang & Huang, Xiaoqiao & Zhang, Zongbin & Li, Chengli & Tai, Yonghang, 2025. "A novel U-LSTM-AFT model for hourly solar irradiance forecasting," Renewable Energy, Elsevier, vol. 238(C).
  90. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org, revised Oct 2024.
  91. Hugo Gobato Souto, 2026. "Evaluating the Efficacy of NHITS for Forecasting Stock Realized Volatility: A Comparative Analysis with Established Models," Computational Economics, Springer;Society for Computational Economics, vol. 67(2), pages 1291-1348, February.
  92. Han Zheng & Junhua Chen & Zhaocha Huang & Kuan Yang & Jianhao Zhu, 2022. "Short-Term Online Forecasting for Passenger Origin–Destination (OD) Flows of Urban Rail Transit: A Graph–Temporal Fused Deep Learning Method," Mathematics, MDPI, vol. 10(19), pages 1-30, October.
  93. Wu, Binrong & Wang, Lin, 2024. "Two-stage decomposition and temporal fusion transformers for interpretable wind speed forecasting," Energy, Elsevier, vol. 288(C).
  94. Kamoona, Ammar & Song, Hui & Jalili, Mahdi & Wang, Hao & Razzaghi, Reza & Yu, Xinghuo, 2025. "Online electric vehicle charging detection based on memory-based transformer using smart meter data," Applied Energy, Elsevier, vol. 398(C).
  95. de Azevedo Takara, Lucas & Teixeira, Ana Clara & Yazdanpanah, Hamed & Mariani, Viviana Cocco & dos Santos Coelho, Leandro, 2024. "Optimizing multi-step wind power forecasting: Integrating advanced deep neural networks with stacking-based probabilistic learning," Applied Energy, Elsevier, vol. 369(C).
  96. Mao, Xuehui & Chen, Shanlin & Yu, Hanxin & Duan, Liwu & He, Yingjie & Chu, Yinghao, 2025. "Simplicity in dynamic and competitive electricity markets: A case study on enhanced linear models versus complex deep-learning models for day-ahead electricity price forecasting," Applied Energy, Elsevier, vol. 383(C).
  97. Le Wang & Boyuan Zhang, 2026. "The Promise of Time-Series Foundation Models for Agricultural Forecasting: Evidence from Commodity Prices," Papers 2601.06371, arXiv.org, revised Jan 2026.
  98. Xu, Rui & Fang, Haoyu & Zeng, Huanze & Wu, Binrong, 2025. "A novel interpretable wind speed forecasting based on the multivariate variational mode decomposition and temporal fusion transformer," Energy, Elsevier, vol. 331(C).
  99. Yunhua Pei & John Cartlidge & Anandadeep Mandal & Daniel Gold & Enrique Marcilio & Riccardo Mazzon, 2025. "Cross-Modal Temporal Fusion for Financial Market Forecasting," Papers 2504.13522, arXiv.org, revised Aug 2025.
  100. Harrison Katz, 2026. "Coupled Supply and Demand Forecasting in Platform Accommodation Markets," Papers 2603.00422, arXiv.org, revised Apr 2026.
  101. Ma, Tian & Wang, Wanwan & Jiang, Fuwei, 2025. "Machine learning the performance of hedge fund," Journal of International Money and Finance, Elsevier, vol. 155(C).
  102. Beckmeyer, Heiner & Wiedemann, Timo, 2022. "Recovering Missing Firm Characteristics with Attention-Based Machine Learning," VfS Annual Conference 2022 (Basel): Big Data in Economics 264135, Verein für Socialpolitik / German Economic Association.
  103. Aleksandr Simonyan, 2024. "BreakGPT: Leveraging Large Language Models for Predicting Asset Price Surges," Papers 2411.06076, arXiv.org.
  104. Shichao Huang & Jing Zhang & Yu He & Xiaofan Fu & Luqin Fan & Gang Yao & Yongjun Wen, 2022. "Short-Term Load Forecasting Based on the CEEMDAN-Sample Entropy-BPNN-Transformer," Energies, MDPI, vol. 15(10), pages 1-14, May.
  105. Liao, Xuan & Wong, Man Sing & Zhu, Rui, 2025. "Dual-gate Temporal Fusion Transformer for estimating large-scale land surface solar irradiation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 214(C).
  106. Pesantez, Jorge E. & Li, Binbin & Lee, Christopher & Zhao, Zhizhen & Butala, Mark & Stillwell, Ashlynn S., 2023. "A Comparison Study of Predictive Models for Electricity Demand in a Diverse Urban Environment," Energy, Elsevier, vol. 283(C).
  107. Miguel López Santos & Xela García-Santiago & Fernando Echevarría Camarero & Gonzalo Blázquez Gil & Pablo Carrasco Ortega, 2022. "Application of Temporal Fusion Transformer for Day-Ahead PV Power Forecasting," Energies, MDPI, vol. 15(14), pages 1-22, July.
  108. Siyi Li & Mingrui Zhang & Robert Doel & Benjamin Ross & Matthew D. Piggott, 2025. "Deep learning predicts real-world electric vehicle direct current charging profiles and durations," Nature Communications, Nature, vol. 16(1), pages 1-13, December.
  109. Denis Levchenko & Efstratios Rappos & Shabnam Ataee & Biagio Nigro & Stephan Robert-Nicoud, 2024. "Chain-structured neural architecture search for financial time series forecasting," Papers 2403.14695, arXiv.org, revised Dec 2024.
  110. Hong, Sungchul & Choi, Yunjin & Jeon, Jong-June, 2025. "Interpretable water level forecaster with spatiotemporal causal attention mechanisms," International Journal of Forecasting, Elsevier, vol. 41(3), pages 1037-1054.
  111. Ullah, Sajid & Chen, Xi & Han, Han & Wu, Junhao & Dong, Jinghan & Liu, Ruiqing & Ding, Weijie & Liu, Min & Li, Qingli & Qi, Honggang & Huang, Yonggui & Yu, Philip Lh, 2025. "A novel hybrid ensemble approach for wind speed forecasting with dual-stage decomposition strategy using optimized GRU and transformer models," Energy, Elsevier, vol. 329(C).
  112. van Zyl, Corne & Ye, Xianming & Naidoo, Raj, 2024. "Harnessing eXplainable artificial intelligence for feature selection in time series energy forecasting: A comparative analysis of Grad-CAM and SHAP," Applied Energy, Elsevier, vol. 353(PA).
  113. Xing, Zhuoqun & Pan, Yiqun & Yang, Yiting & Yuan, Xiaolei & Liang, Yumin & Huang, Zhizhong, 2024. "Transfer learning integrating similarity analysis for short-term and long-term building energy consumption prediction," Applied Energy, Elsevier, vol. 365(C).
  114. Liu, Lei & Wang, Xinyu & Dong, Xue & Chen, Kang & Chen, Qiuju & Li, Bin, 2024. "Interpretable feature-temporal transformer for short-term wind power forecasting with multivariate time series," Applied Energy, Elsevier, vol. 374(C).
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